neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

response modification factor (r factor) is one of the seismic design parameters to be considered in evaluating the performance of buildings during strong motions. this paper has tried to evaluate the response modification factor of concrete coupled shear wall structures with various length/depth ratios of spandrel beams. the effect of diagonal reinforcement of spandrel beam was also evaluated o...

for the nonlinear analysis of structures using the well known newton-raphson method, the tangent stiffness matrices of the elements must be constructed in each iteration. due to the high expense required to find the exact tangent stiffness matrices, researchers have developed novel innovations into the newton-raphson method to reduce the cost and time required by the analysis. in this paper, a ...

in this paper, by investigating the common weights concept and dea models with nonlinear virtual inputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights.

a parametric study is performed to assess the influence of the tension reinforcement index, ( ω = ρ fy /f bc), and the bending moment distribution (loading type) on the ultimate deformation characteristics of reinforced concrete (rc) beams. the analytical results for 15 simply supported beams with different amounts of tension reinforcement ratio under three different loading conditions are pres...

in this article, rubber bumpers of double - wishbone suspension system have been modeled and analyzed. the objective of the present work is to predict the performance of these products during deformation, represent an optimum method to design, obtain stiffness characteristic curves and utilize the results in the automotive suspension dynamic analysis. these parts are nonlinear and exhibit large...

This paper presents first a performance analysis of the recently developed Minimal Resource Allocating Network (MRAN) algorithm for on-line identification of nonlinear dynamic systems. Using nonlinear time invariant and time varying identification benchmark problems, MRAN’s performance is compared with the recently proposed On-line Structural Adaptive Hybrid Learning (ONSAHL) algorithm of Junge...

background: due to embargoes and sanctions from 1979 until 2015, impact on scientific research in iran may be critical. public health is the main example of this burning point. in this paper, the aim was to map the scientific research in public health in iran until 2014 with area studies as well as networks of countries involved. methods: we used bibliographic analyses using vos viewer software...

Several nonlinear adaptive techniques have been proposed for modelling nonlinear channels with memory. These techniques include Volterra series, wavelet networks, neural networks, etc. See [11, 6] for a review. For example, adaptive Volterra series have been applied in [1] for modelling digital satellite channels. These Volterra models do not characterize each element of the channel. They provi...

This paper studies the nonlinear vibration analysis of a simply supported Euler-Bernoulli beam resting on a nonlinear elastic foundation under compressive axial load using nonlinear normal modes concept in the case of three-to-one (3:1) internal resonance. The beam’s governing nonlinear PDE of motion and also its boundary conditions are derived and then solved using the method of Multiple Time ...